Social effects of autonomous driving

How will autonomous driving change local public transport?

On behalf of DB Regio, we worked with our partners to develop three scenarios that illustrate the long-term development, challenges and opportunities of autonomous driving technologies in local public transport.

Efficiency potential for public transport

Prognos examined the economic, ecological and social effects:

Economic effects

• In the public service scenario, annual new car registrations fall by 23 percent, especially for small and compact cars.
• An additional 170,000 autonomous public transport shuttles would be needed each year, opening up a new, high-volume market for vehicle manufacturers.
• The use of an autonomous vehicle fleet in public transport could create 119,000 new jobs, which would offset the loss of driver jobs.

Ecological effects

• In the public service scenario, the vehicle fleet is reduced to 38 million vehicles, which lowers raw material requirements by around 25 percent.
• Up to 440,000 tonnes of materials would be saved annually, including iron and aluminium as well as critical raw materials such as nickel, lithium and cobalt.
• Autonomous shuttles would enable closed material cycles and facilitate the recovery of battery raw materials – up to 10,000 tonnes of graphite and 9,500 tonnes of nickel annually.
• Fewer new registrations could reduce the carbon footprint of vehicle production by 11 percent or 4 million tonnes of CO₂ per year.
• Overall, lower emissions and mileage could avoid economic climate costs of around 3 billion euros per year.

Social effects

• The public service scenario shows that an autonomous public transport fleet enables greater mobility and thus better access to hospitals, shopping facilities and culture.
• Improved mobility could halt migration to the cities – rural areas could gain up to 2.9 million people, mainly young, well-educated skilled workers.
• Autonomous vehicles could prevent 8,000 accidents with personal injury each year; the number of injuries could fall by up to 28,000 and the number of fatalities by up to 200.
• Fewer accidents would lead to savings of around 5 billion euros per year.

Our approach

The study compares three scenarios:

• In the base scenario, traditional public transport will be fully autonomous by 2045.
• The competition scenario builds on the base scenario and adds an additional mobility option: privately operated robot taxis.
• In the public service scenario, road-based public transport is fundamentally upgraded and made more efficient through autonomous vehicles.

A multi-stage approach was chosen for the analysis in order to realistically map the effects of autonomous vehicles on the mobility system. First, future mobility demand was calculated and, based on this, various scenarios for mobility services were developed. This was followed by a microscopic mobility simulation using the Prognos mode choice model: the behaviour of statistically modelled users was simulated in a defined traffic area in order to understand the choice between car, public transport, bicycle or walking. On this basis, the effects on the economy, environment and society were assessed in order to classify the overall social significance of the changes.

Links and downloads

To the study (PDF, in German)

More information on the DB Regio website

Project team: Sven Altenburg, Karuan Aswad, Nico Dietzsch, Dr Oliver Ehrentraut, Markus Hoch, Hannah Staab, Bernhard Wankmüller, Valentin Würth

Last update: 15.01.2026